Lesson 3 of 7 · 16 min
How AI makes things
Goal:See why AI output looks finished, and when not to trust it.
Patterns
Learned from huge amounts of text and images
Your prompt
The only thing it knows about your project
Prediction
Picks the most likely next piece, over and over
Output
Looks finished. Might be wrong.
Under the hood, AI picks the next likely piece, again and again. Play with it.
A poster for a jazz night should feel ____
Low randomness: the most likely word wins almost every time. Predictable, often average.
- moody30%
- smooth22%
- warm16%
- bold12%
- retro10%
- loud6%
- crunchy4%
- Plausible isn't proven. Checking is your job.
- Leave gaps and AI fills them with averages.
- Names, numbers and quotes always need a source.
Five things an AI tool gave you. Use as a starting point, or check first?
Twenty headline ideas for a coffee shop app.
"68% of users abandon carts with more than three steps." No source given.
A summary of five interview transcripts, with three key themes.
Three color palettes for a calm meditation app.
A quote about simplicity from a famous designer.
Because it predicts what's most likely, AI drifts toward the middle of everything it has seen. Ask for "a poster" and you get the average poster, again and again. Every detail you add moves it away from the average and toward your project.
Vague prompt
“Make a poster for an event”
Six versions of the average poster
Specific prompt
“Bold, playful poster for a free student design workshop, date easy to read on a phone, three different directions”
Three directions that fit the brief
Output that looks finished is the easiest kind to wave through. Here's a card an AI drafted from the Design Night brief. Read it like an editor and click every mistake.
Click everything that's wrong. There are four mistakes.
The brief: Design Night, a free evening workshop. Friday, 7pm, in Studio 4.
0 of 4 mistakes found